Academic articles

Capacity Analysis for Aircrew Training Schools - Estimating Optimal Manpower Flows Under Time Varying Policy and Resource Constraints

Capacity analysis for systems with time varying constraints is still an open problem in Operations Research due to the non-stationarity of the problem domain. This is particularly true for Defence manpower supply which is subject to frequent temporal policy and resource changes. As such, the problem cannot be completely covered with a single overriding simulation or optimisation solution, but, rather, better described using piecewise interplay between simulation and optimisation. This paper describes such an approach for a flexible, interactive capacity analysis simulator with an embedded integer linear programming (ILP) optimiser.

Multi-fidelity Simulation Optimisation for Airline Disruption Management

The airline industry faces many causes of disruption. To minimise financial and reputational impact, the airline must adapt its schedules. Due to the complexity of the environment, simulation is a natural modelling approach. However, the large solution space, time constraints and system constraints make the search for revised schedules difficult. This paper presents a method for the aircraft recovery problem that uses multi-fidelity modelling including a trust region simulation optimisation algorithm to mitigate the computational costs of using high-fidelity simulations with its benefits for providing good estimates of the true performance.

A Comprehensive Electricity Market Model Using Simulation And Optimization Techniques

Worldwide Electrical Power Systems (EPSs) are faced with tremendous challenges because of the reduction of greenhouse gas emissions and the increasing number of renewables. EPS analysis can help to show future developments in an uncertain environment and is an important task for the assessment of greenhouse gas emissions. In order to perform such a complex analysis of future EPSs, a huge number of input parameters is needed. Moreover, technical and also economical processes have to be considered. Thereby, one major task is the modeling of electricity markets. In this paper, we present an approach for the modeling of the German EPS including electricity markets using hybrid simulation and mathematical optimization. We contribute an object-oriented electricity market model which can be utilized to study different exchange mechanisms and behavior patterns of generation unit operators. Simulation results show market results for different generation unit operators and realistic market prices.

Simulation-based Headway Optimization for a Subway Network: a Performance Comparison of Population-based Algorithms

This study presents simulation-based optimization for the Viennese subway system. The underlying discrete event simulation model has several stochastic elements like time-dependent demand and turning maneuver times, direction-dependent vehicle travel and passenger travel as well as transfer times. Passenger creation is a Poisson process which uses hourly origin-destination-matrices based on mobile phone data. The number of waiting passengers on platforms and within vehicles are subject to capacity restrictions. As a microscopic element, passenger distribution along platforms and within vehicles is considered. There are trade-offs between service quality (e.g. waiting time) and costs (e.g. fleet mileage). This bi-objective optimization problem is transformed into a single-objective one by normalization and scalarization. The goal is to find optimal time-dependent headways. Computational experience is gained from 48 test instances which are based on real-world data. Several population-based evolutionary algorithms were applied. The covariance matrix adaptation evolution strategy (CMA-ES) performed best.

Hybrid Simulation Challenges and Opportunities: a Life-cycle Approach

The last 10 years have witnessed a marked upsurge of attention on Hybrid Simulation (HS). The majority of authors define HS as a joint modelling approach which includes two or more simulation approaches (mainly Discrete Event Simulation, System Dynamics and Agent Based Simulation). Whilst some may argue that HS has been in existence for more than 5 decades, the recent rise tended to be more problem driven rather than technical experimentation. Winter Simulation Conference (WSC) 2015, 2016, 2017 have witnessed 3 panels on the purpose, history and definition of HS, respectively. This paper reports on a comprehensive review conducted by the panelists on HS and its applications.

A Hybrid Discrete Event Agent Based Overdue Pregnancy Outpatient Clinic Simulation Model

This paper provides an overview of a hybrid, discrete event simulation (DES) agent based model (ABM), simulation model of the overdue pregnancy outpatient clinic at the Obstetrics department of Akershus University Hospital, Norway. The model is being developed in collaboration with clinic staff. The purpose of the model is to better plan resources (e.g. staffing) to improve patient flow at the outpatient clinic given the uncertainty associated with demand. The uncertainty is due to an increase in the size of the hospital’s catchment area, changes to overdue pregnancy guidelines in Norway and that women can give birth before their appointments. The ABM model component represents the human parts of the system, the women and the clinic staff. The DES component represents the outpatient clinic’s physical location and processes/pathways that operate within it. The technicalities of the model are presented along with some illustrative results.

A Multi-method Scheduling Framework for Medical Staff

Hospital planning teams are always concerned with optimizing staffing and scheduling decisions in order to improve hospital performance, patient experience, and staff satisfaction. A multi-method approach including data analytics, modeling and simulation, machine learning, and optimization is proposed to provide a framework for smart and applicable solutions for staffing and shift scheduling. Factors regarding patients, staff, and hospitals are considered in the decision. This framework is piloted using the Emergency Department(ED) of a leading university hospital in Dublin.

Application of Hybrid Simulation Modelling for the Implementation of Job Rotation in a Feedmill

This paper promotes a unique system dynamics-discrete event simulation hybrid modelling framework. The way the hybrid model is developed is intended to simplify the modelling process and make the framework flexible to a variety of situations. In the current study, the framework is used to investigate the success possibility of introducing within-shift job rotation in the plant and its optimal frequency. The intention is to reduce worker exhaustion and by so doing increase productivity and manufacturing throughput.

Optimizing Production Allocation with Simulation in The Fashion Industry: a Multi-Company Case Study

Production Planning and Control (PP&C) has been deeply analyzed in the literature, both in general terms and focusing on specific industries, such as the fashion one. The paper aims to add a contribution in this field presenting an optimization model for the Fashion Supply Chain (FSC), developed considering an interdependent environment composed by a group of focal companies that work with both exclusive and not-exclusive suppliers. The proposed framework will combine simulation and optimization models based on parameters, decision variables, constraints and Objective Functions (OFs) collected through a literature review. The framework has been developed in a parametrical way, in order to fit the peculiarities of the different actors operating along the FSC. The empirical implementation of the framework has been conducted using data coming from fashion companies belonged to the same network, considering rush orders as stochastics events for the scenario analysis and Key Performance Indicators (KPIs) assessment.

Health Care Emergency Plan Modeling and Simulation in Case of Major Flood

Health care system is one of the most critical units in case of disasters. Floods cause an increase of emergency patient flow that may overwhelm hospital resources. In this paper, we present a simulation model that evaluates health care emergency plan and assesses the resilience of the Ile-de-France region in case of a major flood. We combined in the model the health care process with a Markov chain flood model. The results can be used to elaborate an optimized strategy for evacuation and transfer operations. We provide a case study on three specialties and quantify the impact of several flood scenarios on the health care system.